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feat: Shared installation instructions 😈 (#42112)
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
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‎.dockerignore‎

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!common/plugin_transpiler/src
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!common/tailwind
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!dags
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!docs/onboarding
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!ee
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!frontend/@posthog
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!frontend/*.*

‎.github/workflows/docs-preview-trigger.yml‎

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pull_request:
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paths:
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- 'docs/published/**'
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- 'docs/onboarding/**'
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push:
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branches:
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- master
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paths:
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- 'docs/published/**'
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- 'docs/onboarding/**'
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permissions:
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pull-requests: write

‎Dockerfile‎

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COPY common/esbuilder/ common/esbuilder/
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COPY common/tailwind/ common/tailwind/
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COPY products/ products/
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COPY docs/onboarding/ docs/onboarding/
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COPY .git/config .git/config
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COPY .git/HEAD .git/HEAD
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COPY .git/refs/heads .git/refs/heads

‎common/storybook/webpack.config.js‎

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lib: path.resolve(__dirname, '..', '..', 'frontend', 'src', 'lib'),
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scenes: path.resolve(__dirname, '..', '..', 'frontend', 'src', 'scenes'),
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'@posthog/lemon-ui': path.resolve(__dirname, '..', '..', 'frontend', '@posthog', 'lemon-ui', 'src'),
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'@posthog/shared-onboarding': path.resolve(__dirname, '..', '..', 'docs', 'onboarding'),
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storybook: path.resolve(__dirname, '..', '..', 'frontend', '.storybook'),
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types: path.resolve(__dirname, '..', '..', 'frontend', 'types'),
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public: path.resolve(__dirname, '..', '..', 'frontend', 'public'),

‎docs/onboarding/llm-analytics/_snippets/embedding-event.tsx‎

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import { useMDXComponents } from 'scenes/onboarding/OnboardingDocsContentWrapper'
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const propertyColumnStyle = { minWidth: '150px' }
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export const EmbeddingEvent = (): JSX.Element => {
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const { Markdown, dedent } = useMDXComponents()
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return (
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<>
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<Markdown>
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{dedent`
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An embedding is a single call to an embedding model to convert text into a vector representation.
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**Event name**: \`$ai_embedding\`
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### Core properties
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`}
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</Markdown>
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<div className="LemonMarkdown">
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<table className="my-4">
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<thead>
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<tr>
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<th style={propertyColumnStyle}>Property</th>
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<th>Description</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_trace_id</code>
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</td>
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<td>
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<p>
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The trace ID (a UUID to group related AI events together). Must contain only letters, numbers, and special characters: <code>-</code>, <code>_</code>, <code>~</code>, <code>.</code>, <code>@</code>, <code>(</code>, <code>)</code>, <code>!</code>, <code>'</code>, <code>:</code>, <code>|</code>
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<br />
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Example: <code>d9222e05-8708-41b8-98ea-d4a21849e761</code>
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_session_id</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> Groups related traces together. Use this to organize traces by whatever grouping makes sense for your application (user sessions, workflows, conversations, or other logical boundaries).
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<br />
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Example: <code>session-abc-123</code>, <code>conv-user-456</code>
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_span_id</code>
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</td>
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<td>
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<p><em>(Optional)</em> Unique identifier for this embedding operation</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_span_name</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> Name given to this embedding operation
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<br />
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Example: <code>embed_user_query</code>, <code>index_document</code>
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_parent_id</code>
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</td>
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<td>
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<p><em>(Optional)</em> Parent span ID for tree-view grouping</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_model</code>
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</td>
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<td>
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<p>
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The embedding model used
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<br />
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Example: <code>text-embedding-3-small</code>, <code>text-embedding-ada-002</code>
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_provider</code>
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</td>
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<td>
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<p>
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The LLM provider
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<br />
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Example: <code>openai</code>, <code>cohere</code>, <code>voyage</code>
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_input</code>
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</td>
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<td>
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<p>
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The text to embed
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<br />
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Example: <code>"Tell me a fun fact about hedgehogs"</code> or array of strings for batch embeddings
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_input_tokens</code>
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</td>
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<td>
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<p>The number of tokens in the input</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_latency</code>
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</td>
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<td>
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<p><em>(Optional)</em> The latency of the embedding call in seconds</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_http_status</code>
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</td>
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<td>
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<p><em>(Optional)</em> The HTTP status code of the response</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_base_url</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> The base URL of the LLM provider
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<br />
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Example: <code>https://api.openai.com/v1</code>
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_request_url</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> The full URL of the request made to the embedding API
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<br />
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Example: <code>https://api.openai.com/v1/embeddings</code>
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_is_error</code>
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</td>
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<td>
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<p><em>(Optional)</em> Boolean to indicate if the request was an error</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_error</code>
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</td>
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<td>
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<p><em>(Optional)</em> The error message or object if the embedding failed</p>
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</td>
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</tr>
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</tbody>
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</table>
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</div>
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<Markdown>
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{dedent`
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### Cost properties
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Cost properties are optional as we can automatically calculate them from model and token counts. If you want, you can provide your own cost property instead.
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`}
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</Markdown>
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<div className="LemonMarkdown">
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<table className="my-4">
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<thead>
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<tr>
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<th style={propertyColumnStyle}>Property</th>
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<th>Description</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_input_cost_usd</code>
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</td>
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<td>
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<p><em>(Optional)</em> Cost in USD for input tokens</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_output_cost_usd</code>
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</td>
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<td>
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<p><em>(Optional)</em> Cost in USD for output tokens (usually 0 for embeddings)</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_total_cost_usd</code>
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</td>
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<td>
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<p><em>(Optional)</em> Total cost in USD</p>
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</td>
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</tr>
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</tbody>
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</table>
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</div>
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</>
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)
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}
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